• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.127-139
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• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.492-501
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• 2007

Coastal disasters have become one of the most important issues in every coastal country. In Korea, coastal disasters such as storm surge, sea level rise and extreme weather have placed many coastal regions in danger of being exposed or damaged during subsequent storms and gradual shoreline retreat. A storm surge is an onshore gush of water associated with a tow pressure weather system, typically in typhoon season. However, it is very difficult to predict storm surge height and inundation due to the irregularity of the course and intensity of a typhoon. To provide a new scheme of typhoon damage prediction model, the scenario which changes the central pressure, the maximum wind radius, the track and the proceeding speed by corresponding previous typhoon database, was composed. The virtual typhoon scenario database was constructed with individual scenario simulation and evaluation, in which it extracted the result from the scenario database of information of the hereafter typhoon and information due to climate change. This virtual typhoon scenario database will apply damage prediction information about a typhoon. This study performed construction and analysis of the simulation system with the storm surge/coastal inundation model at Masan coastal areas, and applied method for predicting using the scenario of the storm surge.

• Korean Journal of Microbiology
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• v.51 no.2
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• pp.97-107
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• 2015

Wetlands constitute a transitional zone between terrestrial and aquatic ecosystems and have unique characteristics such as frequent inundation, inflow of nutrients from terrestrial ecosystems, presence of plants adapted to grow in water, and soil that is occasionally oxygen deficient due to saturation. These characteristics and the presence of vegetation determine physical and chemical properties that affect decomposition rates of organic matter (OM). Decomposition of OM is associated with activities of various extracellular enzymes (EE) produced by bacteria and fungi. Extracellular enzymes convert macromolecules to simple compounds such as labile organic carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) that can be easily taken up by microbes and plants. Therefore, the enzymatic approach is helpful to understand the decomposition rates of OM and nutrient cycling in wetland soils. This paper reviews the physical and biogeochemical factors that regulate extracellular enzyme activities (EEa) in wetland soils, including those of ${\beta}$-glucosidase, ${\beta}$-N-acetylglucosaminidase, phosphatase, arylsulfatase, and phenol oxidase that decompose organic matter and release C, N, P, and S nutrients for microbial and plant growths. Effects of pH, water table, and particle size of OM on EEa were not significantly different among sites, whereas the influence of temperature on EEa varied depending on microbial acclimation to extreme temperatures. Addition of C, N, or P affected EEa differently depending on the nutrient state, C:N ratio, limiting factors, and types of enzymes of wetland soils. Substrate quality influenced EEa more significantly than did other factors. Also, drainage of wetland and increased temperature due to global climate change can stimulate phenol oxidase activity, and anthropogenic N deposition can enhance the hydrolytic EEa; these effects increase OM decomposition rates and emissions of $CO_2$ and $CH_4$ from wetland systems. The researches on the relationship between microbial structures and EE functions, and environmental factors controlling EEa can be helpful to manipulate wetland ecosystems for treating pollutants and to monitor wetland ecosystem services.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.649-663
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• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.103-110
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• 2019

Recently, Korea has been affected by extreme weather events including extended summers and increased temperatures caused by global warming and climate change. Environmental temperature is especially important to the livestock industry because it is closely related to livestock productivity. This study was conducted to investigate the influence of different environmental temperatures on respiration rate, rectal temperature and body-surface temperature in finishing pigs. Pigs ($98.3{\pm}6.6kg$) were housed in individual cages inside an experimental chamber and exposed continuously to one of five environmental treatments ($22^{\circ}C$, $24^{\circ}C$, $26^{\circ}C$, $28^{\circ}C$, $30^{\circ}C$) for 10 days without providing additional rest time. Feed and water intake, respiration rate, rectal temperature and body-surface (head, ear, neck, back, side) temperature were measured two times daily during the experimental period. A significant increase in respiration rate from $26^{\circ}C$ and in body-surface temperature from $24^{\circ}C$ (p<0.05) was observed. At $30^{\circ}C$, the respiration rate had almost doubled and the body-surface temperature increased by about $5^{\circ}C-7^{\circ}C$. Moreover, ear skin temperature was very sensitive to environmental temperature. However, feed intake, water intake and rectal temperature did not change significantly during the experiment.

• Journal of Christian Education in Korea
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• v.64
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• pp.51-79
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• 2020

This study was conducted to pursue Christian education with the socially underprivileged in the era of the Corona-19 pandemic. Corona-19 is a disaster which is caused, destroyed and exploited by human being. At the time of the indiscriminately spreading global pendemic, we must work together to overcome our selfish self-centeredness and make an attempt for everyone in need. It is a study on how humans can help each other survive in the era of Corona-19 and its post-corona. The problem is that there is too much discrimination between the state, race, and economic capacity, and in the end, the extreme discrimination of capitalism is appeared in society and across the country. There is no significant difference in the confirmation rate when Corona-19 infiltrates, but there is a big difference between those with and less in mortality. As a result, today's reality is that people who have a hard time living because they have less usually are far more vulnerable to blocking and defeating virus attacks. Unfortunately, this is the current situation. From the standpoint of a large discourse, attention is paid to climate change and ecological environment, and as a micro discourse, a number of societies who live with tremendous discrimination according to the gap between the rich and the poor (it is gender, race, disabled, nationality) that exist in almost all countries on the planet. We need attention to the weak. To this end, discourses on vaccine inequality, discourses on the needs of the disabled, discourses on different racial damages, discourses on polarization and dystopia, and discourses on educational inequality were treated as the reality faced by the socially underprivileged in the Corona 19 pandemic. To explore Christian education with the socially underprivileged, to explore ways of sharing, giving, and solidarity for win-win, discourse on inter-dependence and mutual responsibility of mankind, direct counter-measures for the socially underprivileged, and critical literacy education. He proposed a discourse on Korea, a discourse on Homo sapiens, which must return to being a part of creation, and finally a theology of friendship with the weak. Christian education based on Bible words must go forward in the era of the Corona 19 pandemic, hungry, naked, nowhere to go, sick, but dying because of being unable to get a remedy. He emphasized the need to establish a caring theology of friendship and pursue a life in which thought and practice harmonize. Thus, the paper proposed the spirit of Christian education not only doing something for the socially weak, but with the socially weak in the daily life.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.118-130
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• 2024

Rehabilitation of mining areas can reduce damage to ecosystems. However, the effects of rehabilitation on ecosystem services (ESs) and its contribution to local communities are not well known. Thus, the aims of this study were to clearly identify the ES beneficiaries affected by mining activities, to determine how the beneficiaries profit from surrounding areas in cooperation with local stakeholders, and to manage the rehabilitation areas for the ESs that the beneficiaries want. This study chose 18 ESs (4 provisioning, 7 regulating, 5 cultural, and 2 habitat services) based on The Economics of Ecosystems and Biodiversity. A semi-structured questionnaire survey using an 11-point Likert scale was conducted among 87 community residents to investigate social awareness and identify key ESs. The survey results from two local communities showed high awareness and demands mainly on cultural (mental and physical health, aesthetic appreciation, and recreation) and regulating services (local climate and air quality, and moderation of extreme events). These services were related to the daily lives of residents in local communities, provided positive benefits, and potentially improved the residents' future livelihoods. However, the average questionnaire scores were limited to 6-7 points, indicating that the benefits to local communities were meager. The residents' awareness of provisioning service was negative, even if it provided goods and profit opportunities. This indicated a disconnection between local communities and provisioning services due to forest rehabilitation that did not consider local communities that traditionally relied on specific provisioning services before the onset of mining activities. Future forest rehabilitation in abandoned mine areas must consider the welfare of local communities for sustainable use of rehabilitated forests and enhancing ESs. In this study, only a qualitative evaluation based on frequency analyses was conducted. The quantification and valuation of key ESs are warranted in the future to promote ESs from forest rehabilitation in abandoned mine areas. The study results would be useful for developing site-specific ES promotion strategies for reforesting mine areas.